Related Experiment Video
Updated: Apr 5, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Why the C-statistic is not informative to evaluate early warning scores and what metrics to use
Santiago Romero-Brufau1,2, Jeanne M Huddleston3,4,5, Gabriel J Escobar6
1Healthcare Systems Engineering Program, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, 200 First Street SW, Rochester, MN, 55905, USA. RomeroBrufau.Santiago@mayo.edu.
Abstract:
Metrics typically used to report the performance of an early warning score (EWS), such as the area under the receiver operator characteristic curve or C-statistic, are not useful for pre-implementation analyses. Because physiological deterioration has an extremely low prevalence of 0.02 per patient-day, these metrics can be misleading. We discuss the statistical reasoning behind this statement and present a novel alternative metric more adequate to operationalize an EWS. We suggest that pre-implementation evaluation of EWSs should include at least two metrics: sensitivity; and either the positive predictive value, number needed to evaluate, or estimated rate of alerts. We also argue the importance of reporting each individual cutoff value.
More Related Videos
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Decision Making: Traditional Method
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
Receiver Operating Characteristic Plot
Introduction to Nonparametric Statistics
One of...
The Anderson-Darling Test
Detection of Gross Error: The Q Test

